Alba Cervera-Lierta
- Artificial Intelligence top 1%
- Atomic and Molecular Physics, and Optics top 5%
- Computational Theory and Mathematics top 5%
- Electrical and Electronic Engineering
- Materials Chemistry
- Co-authors
- Alán Aspuru‐GuzikAbhinav AnandJakob S. KottmannThi Ha KyawKishor BhartiSukin SimL. C. KwekWai‐Keong Mok
- Topics
- Quantum Information and Cryptography (8 papers)Quantum Computing Algorithms and Architecture (8 papers)Neural Networks and Reservoir Computing (3 papers)
- Cited by
- Artificial IntelligenceAtomic and Molecular Physics, and OpticsComputational Theory and Mathematics
- Partner nations
- CanadaSpainUnited States
In The Last Decade
Alba Cervera-Lierta
10 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 1.1k
- Atomic and Molecular Physics, and Optics 567
- Computational Theory and Mathematics 185
- Electrical and Electronic Engineering 109
- Materials Chemistry 80
Countries citing papers authored by Alba Cervera-Lierta
This map shows the geographic impact of Alba Cervera-Lierta's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alba Cervera-Lierta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alba Cervera-Lierta more than expected).
Fields of papers citing papers by Alba Cervera-Lierta
This network shows the impact of papers produced by Alba Cervera-Lierta. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alba Cervera-Lierta. The network helps show where Alba Cervera-Lierta may publish in the future.
Co-authorship network of co-authors of Alba Cervera-Lierta
This figure shows the co-authorship network connecting the top 25 collaborators of Alba Cervera-Lierta. A scholar is included among the top collaborators of Alba Cervera-Lierta based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alba Cervera-Lierta. Alba Cervera-Lierta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 19 | |
| 3 | Noisy intermediate-scale quantum algorithmsbreakdown → | 955 |
| 4 | On scientific understanding with artificial intelligencebreakdown → | 186 |
| 5 | 4 | |
| 6 | 66 | |
| 7 | 7 | |
| 8 | 13 | |
| 9 | 5 | |
| 10 | 21 | |
| 11 | 16 |
About Alba Cervera-Lierta
Alba Cervera-Lierta is a scholar working on Artificial Intelligence, Information Systems and Management and Biophysics, having authored 11 papers that have together received 1.3k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (8 papers), Quantum Computing Algorithms and Architecture (8 papers) and Neural Networks and Reservoir Computing (3 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Atomic and Molecular Physics, and Optics (567 citations) and Computational Theory and Mathematics (185 citations). Alba Cervera-Lierta has collaborated with scholars based in Canada, Spain and United States. Frequent co-authors include Alán Aspuru‐Guzik, Abhinav Anand, Jakob S. Kottmann, Thi Ha Kyaw, Kishor Bharti, Sukin Sim, L. C. Kwek, Wai‐Keong Mok, Tim Menke and Matthias Degroote. Their work appears in journals such as Reviews of Modern Physics, Physical review. A and Nature Machine Intelligence.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.